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Joint Top-k Subscription Query Processing over Microblog Threads

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Databases Theory and Applications (ADC 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9877))

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Abstract

With an increasing amount of social media messages, users on the social platforms start to seek ideas and opinions by themselves. Publishers/Subscriber queries (a.k.a. pub/sub) are utilized by these who want to actively read and consume web data. Social media platforms give people opportunities to communicate with others. The social property is also important in the pub/sub while currently no other works have ever considered this property. Also, platforms like Twitter only allow users to post a short message which causes the short-text problem: single posts lack of contextual information. Therefore, we propose the microblog thread as the minimum information unit to capture social and textual relevant information. However, this brings several challenges to this problem: 1. How to retrieve the microblog thread while the stream of microblogs keeps updating the microblog threads and the results of subscription queries keep changing? 2. How to represent the subscription results while the microblog threads are frequently updated? Hence, we propose the group filtering and individual filtering to help to satisfy the high update rate of subscription results. Extensive experiments on real datasets have been conducted to verify the efficiency and scalability of our proposed approach.

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Notes

  1. 1.

    https://about.twitter.com/company.

  2. 2.

    http://snap.stanford.edu.

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Correspondence to Liangjun Song .

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Song, L., Bao, Z., Choudhury, F., Sellis, T. (2016). Joint Top-k Subscription Query Processing over Microblog Threads. In: Cheema, M., Zhang, W., Chang, L. (eds) Databases Theory and Applications. ADC 2016. Lecture Notes in Computer Science(), vol 9877. Springer, Cham. https://doi.org/10.1007/978-3-319-46922-5_30

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  • DOI: https://doi.org/10.1007/978-3-319-46922-5_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-46921-8

  • Online ISBN: 978-3-319-46922-5

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